UGC NET — Environmental Sciences (subject code 89) · India · National Testing Agency for the University Grants Commission
Original practice questions written to the published syllabus · not past papersDesigning, analysing and publishing environmental research: hypotheses, field and laboratory designs, long-term experiments, mixed methods, meta-analysis, reproducibility and ethics.
In the exams: UGC NET Paper 1 (research aptitude) and Unit 9; ICAR AICE-JRF/SRF; PhD coursework
How our questions for UGC NET spread across the units of Research Methods in Environmental & Sustainability Science. Difficulty: 29 easy, 48 medium, 16 hard.
| Research questions and hypotheses | 9 | |
| Mixed-effects models and repeated measures | 9 | |
| Multivariate methods in ecology | 9 | |
| Spatial statistics and geostatistics | 9 | |
| Qualitative and participatory methods | 9 | |
| Systematic review and meta-analysis | 9 | |
| Open data, reproducibility and research ethics | 9 | |
| Scientific writing and peer review | 9 | |
| Before-after-control-impact designs | 8 | |
| Long-term experiments and monitoring plots | 7 | |
| Field, plot and landscape-scale experimental designs | 6 |
Choose an answer, then open the working. Each explanation says why the right answer is right and why the others are not.
A test has β = 0.25. What is its power?
B. 0.75
Power = 1 − β = 1 − 0.25 = 0.75. 0.95 and 0.05 confuse power with 1 − α and α.
Further reading: See the manual sources: Hurlbert 1984; Quinn and Keough; Zuur et al.; Legendre and Legendre; Underwood 1994; CEE Guidelines; Koricheva et al.
Moving from many specific field observations to a general statement about a pattern is an example of:
D. Inductive reasoning
Induction generalises from particular cases. Deduction derives specific predictions from a general theory; falsification tests a prediction against data.
Further reading: See the manual sources: Hurlbert 1984; Quinn and Keough; Zuur et al.; Legendre and Legendre; Underwood 1994; CEE Guidelines; Koricheva et al.
For studying the effect of nitrogen deposition on lichens across a region, a gradient design (regression along deposition levels) is often preferred over a few-level ANOVA design because:
A. It yields the shape of the response and more information per sampled site
Sampling many levels lets the response curve and thresholds be estimated. Confounding along gradients must still be handled with covariates or design.
Further reading: See the manual sources: Hurlbert 1984; Quinn and Keough; Zuur et al.; Legendre and Legendre; Underwood 1994; CEE Guidelines; Koricheva et al.
A grouping factor has only three levels (three regions). What is the usual advice?
B. Treat it as a fixed effect, as three levels give a poor variance estimate
Variance among very few levels is estimated poorly; a common rule of thumb is about five or more levels for a random effect.
Further reading: See the manual sources: Hurlbert 1984; Quinn and Keough; Zuur et al.; Legendre and Legendre; Underwood 1994; CEE Guidelines; Koricheva et al.
Quadrat counts of a shrub have a mean of 4 and a variance of 11. The dispersion pattern is most likely:
D. Clumped
Variance-to-mean ratio = 11/4 = 2.75 > 1, indicating aggregation. A Poisson (random) pattern has ratio about 1; regular patterns have ratio < 1.
Further reading: See the manual sources: Hurlbert 1984; Quinn and Keough; Zuur et al.; Legendre and Legendre; Underwood 1994; CEE Guidelines; Koricheva et al.
Why is vote counting (tallying significant versus non-significant studies) discouraged in evidence synthesis?
D. It ignores effect size and precision, penalising small studies
Vote counting treats a small underpowered study's non-significance as evidence against an effect; meta-analysis weights by precision.
Further reading: See the manual sources: Hurlbert 1984; Quinn and Keough; Zuur et al.; Legendre and Legendre; Underwood 1994; CEE Guidelines; Koricheva et al.
A funnel plot of effect size against precision is strongly asymmetric, with small studies showing only large positive effects. This suggests:
C. Possible publication bias or other small-study effects
Missing small studies with null or negative results produce asymmetry; heterogeneity and poor quality in small studies can also do so, so it is suggestive, not proof.
Further reading: See the manual sources: Hurlbert 1984; Quinn and Keough; Zuur et al.; Legendre and Legendre; Underwood 1994; CEE Guidelines; Koricheva et al.
Research misconduct is commonly defined as:
B. Fabrication, falsification and plagiarism
FFP is the core definition; honest error and differences of opinion are explicitly excluded.
Further reading: See the manual sources: Hurlbert 1984; Quinn and Keough; Zuur et al.; Legendre and Legendre; Underwood 1994; CEE Guidelines; Koricheva et al.
Which of the 3Rs is served by using a power analysis to set the minimum number of animals needed in a field study?
A. Reduction
Reduction means using the fewest animals that give valid results. Replacement substitutes non-animal methods; refinement minimises pain and distress.
Further reading: See the manual sources: Hurlbert 1984; Quinn and Keough; Zuur et al.; Legendre and Legendre; Underwood 1994; CEE Guidelines; Koricheva et al.
What does the San Francisco Declaration on Research Assessment (DORA) recommend?
A. Not judging individual researchers by journal metrics like impact factor
DORA (2012) asks that research be assessed on its own merits and that outputs such as datasets and software be valued.
Further reading: See the manual sources: Hurlbert 1984; Quinn and Keough; Zuur et al.; Legendre and Legendre; Underwood 1994; CEE Guidelines; Koricheva et al.
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